1,721,001 research outputs found
Modeling the effects of material chemistry on water flow enhancement in nanotube membranes
No full textAbstract
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Discontinuity Detection by Null Rules for Adaptive Surface Reconstruction
Full text linkWe present a discontinuity detection method based on the so-called null rules, computed as a vector in the null space of certain collocation matrices. These rules are used as weights in a linear combination of function evaluations to indicate the local behavior of the function itself. By analyzing the asymptotic properties of the rules, we introduce two indicators (one for discontinuities of the function and one for discontinuities of its gradient) by locally computing just one rule. This leads to an efficient and reliable scheme, which allows us to effectively detect and classify points close to discontinuities. We then show how this information can be suitably combined with adaptive approximation methods based on hierarchical spline spaces in the reconstruction process of surfaces with discontinuities. The considered adaptive methods exploit the ability of the hierarchical spaces to be locally refined, and fault detection is a natural way to guide the refinement with low computational cost. A selection of test cases is presented to show the effectiveness of our approach
An efficient and reliable quadrature algorithm for integration with respect to binomial measures
No full textPDE models for vegetation biomass and autotoxicity
No full textumerical techniques are widely used to simulate population dynamics in space. In vegetation dynamics, these techniques are very useful to investigate how plants grow, compete for resources, and react to environmental factors within the ecosystem. Plant–soil feedback (PSF) refers to the process where plants or a community alter the biotic and abiotic characteristics of soil that affects the growth of plants or community subsequently growing in that soil. During the last three decades, PSF has been recognized as an important driver for the emergence of vegetation patterns. The importance of studying such vegetation patterns is that they provide an insight into potential ecological changes and illustrate the flexibility and resilience of an ecosystem. Despite the fact that water depletion was once thought to be a major factor in the development of vegetation patterns the existence of patterns in ecosystems without water limitations serves as evidence that this is not the case. In this study, we examine how negative plant–soil feedback contributes to the dynamics of plant biomass. We provide a comparison of different reaction–diffusion PDE models explaining the dynamics of plant biomass in the presence of autotoxicity produced by litter decomposition. We introduce different growth terms, including logistic and exponential, along with additional factors such as extra mortality and inhibitor terms, and develop six distinct models to investigate their individual and combined effects on biomass toxicity distribution. By applying appropriate numerical techniques, we solve the proposed reaction–diffusion PDE models in MATLAB to predict the impact of soil toxicity on plant biomass
Pontryagin Neural Networks for the Class of Optimal Control Problems With Integral Quadratic Cost
Full text linkThis work introduces Pontryagin Neural Networks (PoNNs), a specialised subset of Physics-Informed Neural Networks (PINNs) that aim to learn optimal control actions for optimal control problems (OCPs) characterised by integral quadratic cost functions. PoNNs employ the Pontryagin Minimum Principle (PMP) to establish necessary conditions for optimality, resulting in a two-point boundary value problem (TPBVP) that involves both state and costate variables within a system of ordinary differential equations (ODEs). By modelling the unknown solutions of the TPBVP with neural networks, PoNNs effectively learn the optimal control strategies. We also derive upper bounds on the generalisation error of PoNNs in solving these OCPs, taking into account the selection and quantity of training points along with the training error. To validate our theoretical analysis, we perform numerical experiments on benchmark linear and nonlinear OCPs. The results indicate that PoNNs can successfully learn open-loop control actions for the considered class of OCPs, outperforming the commercial software GPOPS-II in terms of both accuracy and computational efficiency. The reduced computational time suggests that PoNNs hold promise for real-time applications
Enhanced forecasting of Biomass-toxicity-water models using numerical simulations
Full text linkNumerical techniques are essential tools to solve reaction-diffusion models in ecology, addressing the intrinsic complexity arising from nonlinear and coupled systems. Advanced numerical methods provide efficient spatial and temporal resolution in order to predict the emergence of complex patterns, such as the ones arising in vegetation. The emergence of vegetation patterns is significantly influenced by plant-soil feedback, which alters soil properties, shapes nutrient availability, influences plant interactions, and develops mutualistic relationships with soil microbes. Understanding these feedback processes is essential to manage and conserve ecosystems, predict responses to environmental change, and implement appropriate land management strategies. The formation of vegetation patterns has been the focus of significant study and debate over the years and has been linked to two main mechanisms: the depletion of water in the center of vegetation patches and the production of toxicity by litter decomposition in soil. In this study, we investigate the role of water depletion and autotoxicity in the formation of spatial vegetation patterns. We propose and compare various reaction-diffusion PDE models that describe the dynamics of plant biomass under water scarcity and the presence of toxicity caused by litter decomposition. We incorporate logistic and exponential growth functions to capture different growth mechanisms, along with mortality and inhibition terms to simulate the components' individual death rates and inhibitory effects. This leads us to six alternative reaction-diffusion PDE models, which we solve using suitable numerical techniques
New Metropolitan Perspectives. Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030 – Volume 1
No full textThis book explores the role of cities and the urban–rural linkages in spurring innovation embedded in spatial planning, strategic and economic planning, and decision support systems. In particular, the contributions examine the complexity of the current transitional phase towards achieving smart, inclusive and sustainable growth, and investigate the post-2020 UE cohesion policy. The main topics include: Innovation dynamics and smart cities; Urban regeneration – community-led and PPP; Inland and urban area development; Mobility, accessibility, infrastructures; Heritage, landscape and Identity; and Risk management, Environment and Energy. The book includes a selection of articles accepted for presentation and discussion at the 3rd International Symposium New Metropolitan Perspectives (ISTH2020), held at the University of Reggio Calabria, Italy on 22–25 May 2018. The symposium, which addressed the challenge of local knowledge and innovation dynamics towards territory attractiveness, hosted the final event of the MAPS-LED project under Horizon2020 – MSCA RISE
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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